def case_with_zero_value():
kwargs = dict(
a0=[1.0, 3.0],
a=[0.0, 0.0],
aerr=[0.1, 0.76],
acov=[[0.01, 2.3], [2.3, 0.988]],
chi2=8.276,
degrees_of_freedom=5,
)
chi2_reduced = 1.6552
p_probability = 0.14167
arerr = [np.inf, np.inf]
repr_string = """Results:
========
Initial parameters' values:
\t1.0 3.0
Fitted parameters' values:
\ta[0] = 0.0000 \u00B1 0.1000 (inf% error)
\ta[1] = 0.0000 \u00B1 0.7600 (inf% error)
Fitted parameters covariance:
[[0.01 2.3 ]
[2.3 0.988]]
Chi squared: 8.276
Degrees of freedom: 5
Chi squared reduced: 1.655
P-probability: 0.1417
"""
fitting_result = FittingResult(**kwargs)
return (
dict(
chi2_reduced=chi2_reduced,
p_probability=p_probability,
arerr=arerr,
repr_string=repr_string,
delta=10e-5,
**kwargs,
),
fitting_result,
)
def case_with_small_p_probability():
kwargs = dict(
a0=[1.0, 3.0],
a=[1.1, 2.98],
aerr=[0.1, 0.76],
acov=[[0.01, 2.3], [2.3, 0.988]],
chi2=43.726,
degrees_of_freedom=5,
)
chi2_reduced = 8.7452
p_probability = 2.63263e-8
arerr = [9.09091, 25.50336]
repr_string = """Results:
========
Initial parameters' values:
\t1.0 3.0
Fitted parameters' values:
\ta[0] = 1.1000 \u00B1 0.1000 (9.091% error)
\ta[1] = 2.9800 \u00B1 0.7600 (25.50% error)
Fitted parameters covariance:
[[0.01 2.3 ]
[2.3 0.988]]
Chi squared: 43.73
Degrees of freedom: 5
Chi squared reduced: 8.745
P-probability: 2.633e-8
"""
fitting_result = FittingResult(**kwargs)
return (
dict(
chi2_reduced=chi2_reduced,
p_probability=p_probability,
arerr=arerr,
repr_string=repr_string,
delta=10e-5,
**kwargs,
),
fitting_result,
)